The Senate of Romania has authorised legislative packages to advance the review of gambling advertising to be settled by ...

Abstract: The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), ...

Part two of our series, where we take a look back at some of the biggest SBC stories covered on our podcast over the last 12 months.

Harvard's free programming classes teach you how to think, debug, and adapt in an AI-driven world where knowing code matters more than ever.

A critical LangChain AI vulnerability exposes millions of apps to theft and code injection, prompting urgent patching and ...

Abstract: The past decade has witnessed the success of deep learning-based multivariate time-series forecasting in Internet of Things (IoT) systems. However, dynamic variable correlation remains a ...

Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...

Toto is a foundation model for multivariate time series forecasting with a focus on observability metrics. This model leverages innovative architectural designs to efficiently handle the ...

What is Singular Spectrum Analysis (SSA)? Singular Spectrum Analysis (SSA) is a non-parametric technique in machine learning used to analyze and forecast time series data. SSA decomposes a time series ...

Despite being despised by large swathes of football supporters, VAR is here to stay, and 2024–25 was another turbulent campaign for the technology and its users in the Premier League. During its fifth ...